Mobile video data collection equipment was used to collect data and determine traffic flow and roadway surface conditions during seven winter weather events. Driver visibility was estimated manually. The use of the mobile video data collection equipment in this research and some concerns related to its use during winter weather are discussed. The characteristics of the data are summarized, and the results of a multiple regression statistical analysis presented. Winter weather data were collected and summarized by 15-min time periods. The data included traffic volumes, vehicle speeds, vehicle gaps or headways, visibility, and roadway snow cover. The average winter weather vehicle speed was significantly lower than normal, and multiple regression indicated a relationship among the average off-peak winter weather vehicle speed, the square of hourly volume, visibility, and roadway snow cover. The traffic volume variable in this model was believed to be a surrogate for weather data not collected. The model predicts that visibility below 0.4 km (0.25 mi) and snow cover on the roadway lanes may reduce average off-peak winter weather vehicle speeds by approximately 6.3 and 11.7 km/h (3.9 and 7.3 mph), respectively. It was concluded that the collection of traffic flow and roadway surface data during winter weather events requires the seamless integration, planning, and calibration of a partially video-based automated permanent or semipermanent information system. The ability to assess, quantify, and communicate the potential vehicle speed effects of winter weather could assist drivers with travel decisions and public-sector workers with maintenance decisions.